Urology

Leveraging Representation Learning for Bi-parametric Prostate MRI to Disambiguate PI-RADS 3 and Improve Biopsy Decision Strategies.

OBJECTIVES: Despite its high negative predictive value (NPV) for clinically significant prostate can...

Correction to "Machine Learning-Enhanced Structure-Based Gaussian Expansion for Efficient Wavepacket Calculations".

Letter to editor: an artificial intelligence model for nuclear grading of clear cell renal cell carcinoma using whole slide images: a retrospective, multicentre, diagnostic study.

Letter to the editor regarding "an artificial intelligence model for nuclear grading of clear cell renal cell carcinoma using whole slide images: a retrospective, multicentre, diagnostic study".

Machine learning-based comparison of transperineal vs. transrectal biopsy for prostate cancer diagnosis: evaluating procedural effectiveness.

BACKGROUND: Transrectal (TR) and transperineal (TP) biopsies are commonly used methods for diagnosin...

Unraveling the role of perineural invasion in cancer progression across multiple tumor types.

Perineural invasion (PNI) refers to the infiltration of tumor cells into the connective tissue of ne...

From laser-on time to lithotripsy duration: improving the prediction of lithotripsy duration with 'Kidney Stone Calculator' using artificial intelligence.

INTRODUCTION: "Kidney Stone Calculator" (KSC) helps to plan flexible ureteroscopy, providing the sto...

Non-conventional diagnostic tools for lower urinary tract symptoms and bladder outlet obstruction in men: a perspective review.

Introduction Assessing male lower urinary tract symptoms (LUTS) due to Benign outlet obstruction (BO...

A new method for internal urinary metabolite exposure and dietary exposure association assessment of 3-MCPD and glycidol and their esters based on machine learning.

3-Monochloropropane-1,2-diol (3-MCPD) and glycidol along with their esters are commonly found in che...

Integrated transcriptome analysis and combinatorial machine learning to construct a homeostatic model of acetylation for ccRCC and validate the key gene GCNT4.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors of th...

Few-Shot Learning for Prostate Cancer Detection on MRI: Comparative Analysis with Radiologists' Performance.

Deep-learning models for prostate cancer detection typically require large datasets, limiting clinic...

Sex differences in serum proteomic profiles in psoriatic arthritis.

OBJECTIVES: Sex-related differences exist in the clinical presentation and treatment outcomes of pat...

Renal Dysfunction Across the Spectrum of Cardiogenic Shock: Mechanisms, Clinical Implications, and Therapeutic Strategies.

PURPOSE OF REVIEW: This review aims to elucidate the complex interplay between cardiogenic shock (CS...

Prospective cohort study integrating plasma proteomics and machine learning for early risk prediction of prostate cancer.

BACKGROUND: Early detection of prostate cancer (PCa) remains a clinical challenge. Plasma proteomics...

Efficient calculations of impurity diffusivity in metals by linearized multi-band embedded atom method potentials.

Impurity diffusivity in metals has attracted much attention in materials science and engineering due...

Correction to: Recognition of intraglomerular histological features with deep learning in protocol transplant biopsies and their association with kidney function and prognosis.

[This corrects the article DOI: 10.1093/ckj/sfae019.].

Machine learning model for the prediction of postoperative acute kidney injury (AKI) in neonates undergoing digestive surgery.

OBJECTIVE: The aim of our study is to determine the main predictors of postoperative AKI in neonates...

Machine learning-based construction and validation of an radiomics model for predicting ISUP grading in prostate cancer: a multicenter radiomics study based on [68Ga]Ga-PSMA PET/CT.

PURPOSE: The International Society of Urological Pathology (ISUP) grading of prostate cancer (PCa) i...

Reply Letter to Dr. Kumar et al. on: Enhanced Artificial Intelligence in Bladder Cancer Management: A Comparative Analysis and Optimization Study of Multiple Large Language Models.

Exploring the association between volatile organic compound exposure and chronic kidney disease: evidence from explainable machine learning methods.

BACKGROUND: Chronic Kidney Disease (CKD) affects approximately 697.5 million people worldwide. Volat...

MRI Radiomics and Automated Habitat Analysis Enhance Machine Learning Prediction of Bone Metastasis and High-Grade Gleason Scores in Prostate Cancer.

RATIONALE AND OBJECTIVES: To explore the value of machine learning models based on MRI radiomics and...